(base) C:\Users\andreas>conda env remove --name compvis 

(base) C:\Users\andreas>conda create --name compvis python=3.7

Collecting package metadata (current_repodata.json): done
Solving environment: done

## Package Plan ##

  environment location: C:\Users\andreas\Miniconda3\envs\compvis

  added / updated specs:
    - python=3.7


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    python-3.7.7               |h60c2a47_0_cpython        14.8 MB
    ------------------------------------------------------------
                                           Total:        14.8 MB

The following NEW packages will be INSTALLED:

  ca-certificates    pkgs/main/win-64::ca-certificates-2020.1.1-0
  certifi            pkgs/main/win-64::certifi-2019.11.28-py37_1
  openssl            pkgs/main/win-64::openssl-1.1.1e-he774522_0
  pip                pkgs/main/win-64::pip-20.0.2-py37_1
  python             pkgs/main/win-64::python-3.7.7-h60c2a47_0_cpython
  setuptools         pkgs/main/win-64::setuptools-46.1.3-py37_0
  sqlite             pkgs/main/win-64::sqlite-3.31.1-he774522_0
  vc                 pkgs/main/win-64::vc-14.1-h0510ff6_4
  vs2015_runtime     pkgs/main/win-64::vs2015_runtime-14.16.27012-hf0eaf9b_1
  wheel              pkgs/main/win-64::wheel-0.34.2-py37_0
  wincertstore       pkgs/main/win-64::wincertstore-0.2-py37_0


Proceed ([y]/n)? y


Downloading and Extracting Packages
python-3.7.7         | 14.8 MB   | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
#     $ conda activate compvis
#
# To deactivate an active environment, use
#
#     $ conda deactivate

(base) C:\Users\andreas>conda activate compvis
(compvis) C:\Users\andreas>conda install -c conda-forge jupyter scikit-learn scikit-image matplotlib ipywidgets tqdm keras notebook seaborn pandas opencv

Collecting package metadata (current_repodata.json): done
Solving environment: done

## Package Plan ##

  environment location: C:\Users\andreas\Miniconda3\envs\compvis

  added / updated specs:
    - ipywidgets
    - jupyter
    - keras
    - matplotlib
    - notebook
    - scikit-image
    - scikit-learn
    - tqdm


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    _tflow_select-2.2.0        |            eigen           3 KB
    absl-py-0.9.0              |   py37hc8dfbb8_1         162 KB  conda-forge
    bleach-3.1.4               |     pyh9f0ad1d_0         111 KB  conda-forge
    blinker-1.4                |             py_1          13 KB  conda-forge
    cachetools-3.1.1           |             py_0          11 KB  conda-forge
    certifi-2019.11.28         |   py37hc8dfbb8_1         149 KB  conda-forge
    cffi-1.14.0                |   py37ha419a9e_0         222 KB  conda-forge
    chardet-3.0.4              |py37hc8dfbb8_1006         189 KB  conda-forge
    click-7.1.1                |     pyh8c360ce_0          64 KB  conda-forge
    cryptography-2.8           |   py37hb32ad35_1         564 KB  conda-forge
    cytoolz-0.10.1             |   py37hfa6e2cd_0         336 KB  conda-forge
    dask-core-2.13.0           |             py_0         596 KB  conda-forge
    entrypoints-0.3            |py37hc8dfbb8_1001          12 KB  conda-forge
    freetype-2.10.1            |       ha9979f8_0         481 KB  conda-forge
    gast-0.2.2                 |             py_0          10 KB  conda-forge
    google-auth-1.12.0         |     pyh9f0ad1d_0          52 KB  conda-forge
    google-auth-oauthlib-0.4.1 |             py_2          18 KB  conda-forge
    google-pasta-0.2.0         |     pyh8c360ce_0          42 KB  conda-forge
    grpcio-1.27.2              |   py37h351948d_0         1.2 MB
    h5py-2.10.0                |nompi_py37h422b98e_102         950 KB  conda-forge
    idna-2.9                   |             py_1          52 KB  conda-forge
    importlib-metadata-1.6.0   |   py37hc8dfbb8_0          42 KB  conda-forge
    importlib_metadata-1.6.0   |                0           3 KB  conda-forge
    ipykernel-5.2.0            |   py37h5ca1d4c_1         161 KB  conda-forge
    ipython-7.13.0             |   py37hc8dfbb8_2         1.1 MB  conda-forge
    jedi-0.16.0                |   py37hc8dfbb8_1         772 KB  conda-forge
    jsonschema-3.2.0           |   py37hc8dfbb8_1         108 KB  conda-forge
    jupyter_client-6.1.2       |             py_0          74 KB  conda-forge
    jupyter_console-6.1.0      |             py_1          21 KB  conda-forge
    jupyter_core-4.6.3         |   py37hc8dfbb8_1          94 KB  conda-forge
    keras-2.3.1                |   py37h21ff451_0         591 KB  conda-forge
    kiwisolver-1.1.0           |   py37heaa310e_1          61 KB  conda-forge
    libpng-1.6.37              |       hfe6a214_1         1.4 MB  conda-forge
    libtiff-4.1.0              |       h885aae3_6        1020 KB  conda-forge
    markupsafe-1.1.1           |   py37h8055547_1          28 KB  conda-forge
    matplotlib-3.2.1           |                0           6 KB  conda-forge
    matplotlib-base-3.2.1      |   py37h911224e_0         7.1 MB  conda-forge
    mistune-0.8.4              |py37hfa6e2cd_1000          53 KB  conda-forge
    mkl-service-2.3.0          |   py37hb782905_0         210 KB
    nbconvert-5.6.1            |           py37_0         506 KB  conda-forge
    notebook-6.0.3             |           py37_0         7.7 MB  conda-forge
    numpy-1.18.1               |   py37h90d3380_1         4.7 MB  conda-forge
    oauthlib-3.0.1             |             py_0          82 KB  conda-forge
    opt_einsum-3.2.0           |             py_0          49 KB  conda-forge
    pickleshare-0.7.5          |py37hc8dfbb8_1001          12 KB  conda-forge
    pillow-7.0.0               |   py37h91e7a8d_1         700 KB  conda-forge
    prompt-toolkit-3.0.5       |             py_0         232 KB  conda-forge
    prompt_toolkit-3.0.5       |                0           4 KB  conda-forge
    protobuf-3.11.4            |   py37he025d50_0         583 KB  conda-forge
    pyasn1-0.4.8               |             py_0          53 KB  conda-forge
    pyasn1-modules-0.2.7       |             py_0          60 KB  conda-forge
    pycparser-2.20             |             py_0          89 KB  conda-forge
    pygpu-0.7.6                |py37hc8d92b1_1000         600 KB  conda-forge
    pyjwt-1.7.1                |             py_0          17 KB  conda-forge
    pyopenssl-19.1.0           |             py_1          47 KB  conda-forge
    pyqt-5.12.3                |   py37h6538335_1         4.7 MB  conda-forge
    pyreadline-2.1             |        py37_1001         141 KB  conda-forge
    pyrsistent-0.16.0          |   py37h8055547_0          91 KB  conda-forge
    pysocks-1.7.1              |   py37hc8dfbb8_1          27 KB  conda-forge
    python_abi-3.7             |          1_cp37m           4 KB  conda-forge
    pywavelets-1.1.1           |   py37hc8d92b1_0         4.3 MB  conda-forge
    pywin32-227                |   py37hfa6e2cd_0         7.0 MB  conda-forge
    pywinpty-0.5.7             |           py37_0          48 KB  conda-forge
    pyyaml-5.3.1               |   py37h8055547_0         155 KB  conda-forge
    pyzmq-19.0.0               |   py37h8c16cda_1         428 KB  conda-forge
    qtconsole-4.7.2            |     pyh9f0ad1d_0          87 KB  conda-forge
    requests-2.23.0            |     pyh8c360ce_2          47 KB  conda-forge
    requests-oauthlib-1.2.0    |             py_0          19 KB  conda-forge
    rsa-4.0                    |             py_0          27 KB  conda-forge
    scikit-image-0.16.2        |   py37he350917_0        24.1 MB  conda-forge
    scikit-learn-0.22.2.post1  |   py37h7208079_0         6.1 MB  conda-forge
    scipy-1.4.1                |   py37h9439919_0        11.9 MB
    six-1.14.0                 |             py_1          13 KB  conda-forge
    tensorboard-2.1.0          |            py3_0         3.3 MB
    tensorflow-2.1.0           |eigen_py37hd727fc0_0           4 KB
    tensorflow-base-2.1.0      |eigen_py37h49b2757_0        35.4 MB
    tensorflow-estimator-2.1.0 |     pyhd54b08b_0         251 KB
    terminado-0.8.3            |   py37hc8dfbb8_1          23 KB  conda-forge
    theano-1.0.4               |py37h6538335_1001         3.7 MB  conda-forge
    tornado-6.0.4              |   py37hfa6e2cd_0         643 KB  conda-forge
    traitlets-4.3.3            |   py37hc8dfbb8_1         133 KB  conda-forge
    urllib3-1.25.7             |   py37hc8dfbb8_1         160 KB  conda-forge
    wcwidth-0.1.9              |     pyh9f0ad1d_0          20 KB  conda-forge
    werkzeug-0.16.1            |             py_0         255 KB  conda-forge
    widgetsnbextension-3.5.1   |           py37_0         1.8 MB  conda-forge
    win_inet_pton-1.1.0        |           py37_0           7 KB  conda-forge
    wrapt-1.12.1               |   py37h8055547_1          45 KB  conda-forge
    xz-5.2.4                   |    h2fa13f4_1002         815 KB  conda-forge
    zstd-1.4.4                 |       hd8a0e53_2         1.7 MB  conda-forge
    ------------------------------------------------------------
                                           Total:       140.6 MB

The following NEW packages will be INSTALLED:

  _tflow_select      pkgs/main/win-64::_tflow_select-2.2.0-eigen
  absl-py            conda-forge/win-64::absl-py-0.9.0-py37hc8dfbb8_1
  astor              conda-forge/noarch::astor-0.7.1-py_0
  attrs              conda-forge/noarch::attrs-19.3.0-py_0
  backcall           conda-forge/noarch::backcall-0.1.0-py_0
  blas               pkgs/main/win-64::blas-1.0-mkl
  bleach             conda-forge/noarch::bleach-3.1.4-pyh9f0ad1d_0
  blinker            conda-forge/noarch::blinker-1.4-py_1
  cachetools         conda-forge/noarch::cachetools-3.1.1-py_0
  cffi               conda-forge/win-64::cffi-1.14.0-py37ha419a9e_0
  chardet            conda-forge/win-64::chardet-3.0.4-py37hc8dfbb8_1006
  click              conda-forge/noarch::click-7.1.1-pyh8c360ce_0
  cloudpickle        conda-forge/noarch::cloudpickle-1.3.0-py_0
  colorama           conda-forge/noarch::colorama-0.4.3-py_0
  cryptography       conda-forge/win-64::cryptography-2.8-py37hb32ad35_1
  cycler             conda-forge/noarch::cycler-0.10.0-py_2
  cytoolz            conda-forge/win-64::cytoolz-0.10.1-py37hfa6e2cd_0
  dask-core          conda-forge/noarch::dask-core-2.13.0-py_0
  decorator          conda-forge/noarch::decorator-4.4.2-py_0
  defusedxml         conda-forge/noarch::defusedxml-0.6.0-py_0
  entrypoints        conda-forge/win-64::entrypoints-0.3-py37hc8dfbb8_1001
  freetype           conda-forge/win-64::freetype-2.10.1-ha9979f8_0
  gast               conda-forge/noarch::gast-0.2.2-py_0
  google-auth        conda-forge/noarch::google-auth-1.12.0-pyh9f0ad1d_0
  google-auth-oauth~ conda-forge/noarch::google-auth-oauthlib-0.4.1-py_2
  google-pasta       conda-forge/noarch::google-pasta-0.2.0-pyh8c360ce_0
  grpcio             pkgs/main/win-64::grpcio-1.27.2-py37h351948d_0
  h5py               conda-forge/win-64::h5py-2.10.0-nompi_py37h422b98e_102
  hdf5               conda-forge/win-64::hdf5-1.10.5-nompi_ha405e13_1104
  icc_rt             pkgs/main/win-64::icc_rt-2019.0.0-h0cc432a_1
  icu                conda-forge/win-64::icu-64.2-he025d50_1
  idna               conda-forge/noarch::idna-2.9-py_1
  imageio            conda-forge/noarch::imageio-2.8.0-py_0
  importlib-metadata conda-forge/win-64::importlib-metadata-1.6.0-py37hc8dfbb8_0
  importlib_metadata conda-forge/noarch::importlib_metadata-1.6.0-0
  intel-openmp       pkgs/main/win-64::intel-openmp-2020.0-166
  ipykernel          conda-forge/win-64::ipykernel-5.2.0-py37h5ca1d4c_1
  ipython            conda-forge/win-64::ipython-7.13.0-py37hc8dfbb8_2
  ipython_genutils   conda-forge/noarch::ipython_genutils-0.2.0-py_1
  ipywidgets         conda-forge/noarch::ipywidgets-7.5.1-py_0
  jedi               conda-forge/win-64::jedi-0.16.0-py37hc8dfbb8_1
  jinja2             conda-forge/noarch::jinja2-2.11.1-py_0
  joblib             conda-forge/noarch::joblib-0.14.1-py_0
  jpeg               conda-forge/win-64::jpeg-9c-hfa6e2cd_1001
  jsonschema         conda-forge/win-64::jsonschema-3.2.0-py37hc8dfbb8_1
  jupyter            conda-forge/noarch::jupyter-1.0.0-py_2
  jupyter_client     conda-forge/noarch::jupyter_client-6.1.2-py_0
  jupyter_console    conda-forge/noarch::jupyter_console-6.1.0-py_1
  jupyter_core       conda-forge/win-64::jupyter_core-4.6.3-py37hc8dfbb8_1
  keras              conda-forge/win-64::keras-2.3.1-py37h21ff451_0
  keras-applications conda-forge/noarch::keras-applications-1.0.8-py_1
  keras-preprocessi~ conda-forge/noarch::keras-preprocessing-1.1.0-py_0
  kiwisolver         conda-forge/win-64::kiwisolver-1.1.0-py37heaa310e_1
  libblas            conda-forge/win-64::libblas-3.8.0-15_mkl
  libcblas           conda-forge/win-64::libcblas-3.8.0-15_mkl
  libclang           conda-forge/win-64::libclang-9.0.1-default_hf44288c_0
  libgpuarray        conda-forge/win-64::libgpuarray-0.7.6-hfa6e2cd_1003
  liblapack          conda-forge/win-64::liblapack-3.8.0-15_mkl
  libpng             conda-forge/win-64::libpng-1.6.37-hfe6a214_1
  libprotobuf        conda-forge/win-64::libprotobuf-3.11.4-h1a1b453_0
  libsodium          conda-forge/win-64::libsodium-1.0.17-h2fa13f4_0
  libtiff            conda-forge/win-64::libtiff-4.1.0-h885aae3_6
  lz4-c              conda-forge/win-64::lz4-c-1.8.3-he025d50_1001
  m2w64-gcc-libgfor~ pkgs/msys2/win-64::m2w64-gcc-libgfortran-5.3.0-6
  m2w64-gcc-libs     pkgs/msys2/win-64::m2w64-gcc-libs-5.3.0-7
  m2w64-gcc-libs-co~ pkgs/msys2/win-64::m2w64-gcc-libs-core-5.3.0-7
  m2w64-gmp          pkgs/msys2/win-64::m2w64-gmp-6.1.0-2
  m2w64-libwinpthre~ pkgs/msys2/win-64::m2w64-libwinpthread-git-5.0.0.4634.697f757-2
  mako               conda-forge/noarch::mako-1.1.0-py_0
  markdown           conda-forge/noarch::markdown-3.2.1-py_0
  markupsafe         conda-forge/win-64::markupsafe-1.1.1-py37h8055547_1
  matplotlib         conda-forge/win-64::matplotlib-3.2.1-0
  matplotlib-base    conda-forge/win-64::matplotlib-base-3.2.1-py37h911224e_0
  mistune            conda-forge/win-64::mistune-0.8.4-py37hfa6e2cd_1000
  mkl                pkgs/main/win-64::mkl-2020.0-166
  mkl-service        pkgs/main/win-64::mkl-service-2.3.0-py37hb782905_0
  msys2-conda-epoch  pkgs/msys2/win-64::msys2-conda-epoch-20160418-1
  nbconvert          conda-forge/win-64::nbconvert-5.6.1-py37_0
  nbformat           conda-forge/noarch::nbformat-5.0.4-py_0
  networkx           conda-forge/noarch::networkx-2.4-py_1
  notebook           conda-forge/win-64::notebook-6.0.3-py37_0
  numpy              conda-forge/win-64::numpy-1.18.1-py37h90d3380_1
  oauthlib           conda-forge/noarch::oauthlib-3.0.1-py_0
  olefile            conda-forge/noarch::olefile-0.46-py_0
  opt_einsum         conda-forge/noarch::opt_einsum-3.2.0-py_0
  pandoc             conda-forge/win-64::pandoc-2.9.2-0
  pandocfilters      conda-forge/noarch::pandocfilters-1.4.2-py_1
  parso              conda-forge/noarch::parso-0.6.2-py_0
  pickleshare        conda-forge/win-64::pickleshare-0.7.5-py37hc8dfbb8_1001
  pillow             conda-forge/win-64::pillow-7.0.0-py37h91e7a8d_1
  prometheus_client  conda-forge/noarch::prometheus_client-0.7.1-py_0
  prompt-toolkit     conda-forge/noarch::prompt-toolkit-3.0.5-py_0
  prompt_toolkit     conda-forge/noarch::prompt_toolkit-3.0.5-0
  protobuf           conda-forge/win-64::protobuf-3.11.4-py37he025d50_0
  pyasn1             conda-forge/noarch::pyasn1-0.4.8-py_0
  pyasn1-modules     conda-forge/noarch::pyasn1-modules-0.2.7-py_0
  pycparser          conda-forge/noarch::pycparser-2.20-py_0
  pygments           conda-forge/noarch::pygments-2.6.1-py_0
  pygpu              conda-forge/win-64::pygpu-0.7.6-py37hc8d92b1_1000
  pyjwt              conda-forge/noarch::pyjwt-1.7.1-py_0
  pyopenssl          conda-forge/noarch::pyopenssl-19.1.0-py_1
  pyparsing          conda-forge/noarch::pyparsing-2.4.6-py_0
  pyqt               conda-forge/win-64::pyqt-5.12.3-py37h6538335_1
  pyreadline         conda-forge/win-64::pyreadline-2.1-py37_1001
  pyrsistent         conda-forge/win-64::pyrsistent-0.16.0-py37h8055547_0
  pysocks            conda-forge/win-64::pysocks-1.7.1-py37hc8dfbb8_1
  python-dateutil    conda-forge/noarch::python-dateutil-2.8.1-py_0
  python_abi         conda-forge/win-64::python_abi-3.7-1_cp37m
  pywavelets         conda-forge/win-64::pywavelets-1.1.1-py37hc8d92b1_0
  pywin32            conda-forge/win-64::pywin32-227-py37hfa6e2cd_0
  pywinpty           conda-forge/win-64::pywinpty-0.5.7-py37_0
  pyyaml             conda-forge/win-64::pyyaml-5.3.1-py37h8055547_0
  pyzmq              conda-forge/win-64::pyzmq-19.0.0-py37h8c16cda_1
  qt                 conda-forge/win-64::qt-5.12.5-h7ef1ec2_0
  qtconsole          conda-forge/noarch::qtconsole-4.7.2-pyh9f0ad1d_0
  qtpy               conda-forge/noarch::qtpy-1.9.0-py_0
  requests           conda-forge/noarch::requests-2.23.0-pyh8c360ce_2
  requests-oauthlib  conda-forge/noarch::requests-oauthlib-1.2.0-py_0
  rsa                conda-forge/noarch::rsa-4.0-py_0
  scikit-image       conda-forge/win-64::scikit-image-0.16.2-py37he350917_0
  scikit-learn       conda-forge/win-64::scikit-learn-0.22.2.post1-py37h7208079_0
  scipy              pkgs/main/win-64::scipy-1.4.1-py37h9439919_0
  send2trash         conda-forge/noarch::send2trash-1.5.0-py_0
  six                conda-forge/noarch::six-1.14.0-py_1
  tensorboard        pkgs/main/noarch::tensorboard-2.1.0-py3_0
  tensorflow         pkgs/main/win-64::tensorflow-2.1.0-eigen_py37hd727fc0_0
  tensorflow-base    pkgs/main/win-64::tensorflow-base-2.1.0-eigen_py37h49b2757_0
  tensorflow-estima~ pkgs/main/noarch::tensorflow-estimator-2.1.0-pyhd54b08b_0
  termcolor          conda-forge/noarch::termcolor-1.1.0-py_2
  terminado          conda-forge/win-64::terminado-0.8.3-py37hc8dfbb8_1
  testpath           conda-forge/noarch::testpath-0.4.4-py_0
  theano             conda-forge/win-64::theano-1.0.4-py37h6538335_1001
  tk                 conda-forge/win-64::tk-8.6.10-hfa6e2cd_0
  toolz              conda-forge/noarch::toolz-0.10.0-py_0
  tornado            conda-forge/win-64::tornado-6.0.4-py37hfa6e2cd_0
  tqdm               conda-forge/noarch::tqdm-4.44.1-pyh9f0ad1d_0
  traitlets          conda-forge/win-64::traitlets-4.3.3-py37hc8dfbb8_1
  urllib3            conda-forge/win-64::urllib3-1.25.7-py37hc8dfbb8_1
  vs2015_win-64      pkgs/main/win-64::vs2015_win-64-14.0.25420-h55c1224_11
  wcwidth            conda-forge/noarch::wcwidth-0.1.9-pyh9f0ad1d_0
  webencodings       conda-forge/noarch::webencodings-0.5.1-py_1
  werkzeug           conda-forge/noarch::werkzeug-0.16.1-py_0
  widgetsnbextension conda-forge/win-64::widgetsnbextension-3.5.1-py37_0
  win_inet_pton      conda-forge/win-64::win_inet_pton-1.1.0-py37_0
  winpty             conda-forge/win-64::winpty-0.4.3-4
  wrapt              conda-forge/win-64::wrapt-1.12.1-py37h8055547_1
  xz                 conda-forge/win-64::xz-5.2.4-h2fa13f4_1002
  yaml               conda-forge/win-64::yaml-0.2.2-hfa6e2cd_1
  zeromq             conda-forge/win-64::zeromq-4.3.2-h6538335_2
  zipp               conda-forge/noarch::zipp-3.1.0-py_0
  zlib               conda-forge/win-64::zlib-1.2.11-h2fa13f4_1006
  zstd               conda-forge/win-64::zstd-1.4.4-hd8a0e53_2

The following packages will be SUPERSEDED by a higher-priority channel:

  ca-certificates     pkgs/main::ca-certificates-2020.1.1-0 --> conda-forge::ca-certificates-2019.11.28-hecc5488_0
  certifi              pkgs/main::certifi-2019.11.28-py37_1 --> conda-forge::certifi-2019.11.28-py37hc8dfbb8_1
  openssl              pkgs/main::openssl-1.1.1e-he774522_0 --> conda-forge::openssl-1.1.1e-hfa6e2cd_0


Proceed ([y]/n)? y


Downloading and Extracting Packages
python_abi-3.7       | 4 KB      | ################### | 100%
ipython-7.13.0       | 1.1 MB    | ################### | 100%
pyzmq-19.0.0         | 428 KB    | ################### | 100%
werkzeug-0.16.1      | 255 KB    | ################### | 100%
google-pasta-0.2.0   | 42 KB     | ################### | 100%
matplotlib-base-3.2. | 7.1 MB    | ################### | 100%
urllib3-1.25.7       | 160 KB    | ################### | 100%
importlib_metadata-1 | 3 KB      | ################### | 100%
h5py-2.10.0          | 950 KB    | ################### | 100%
jupyter_core-4.6.3   | 94 KB     | ################### | 100%
six-1.14.0           | 13 KB     | ################### | 100%
matplotlib-3.2.1     | 6 KB      | ################### | 100%
idna-2.9             | 52 KB     | ################### | 100%
libtiff-4.1.0        | 1020 KB   | ################### | 100%
scipy-1.4.1          | 11.9 MB   | ################### | 100%
pyasn1-0.4.8         | 53 KB     | ################### | 100%
tensorflow-base-2.1. | 35.4 MB   | ################### | 100%
prompt_toolkit-3.0.5 | 4 KB      | ################### | 100%
certifi-2019.11.28   | 149 KB    | ################### | 100%
ipykernel-5.2.0      | 161 KB    | ################### | 100%
oauthlib-3.0.1       | 82 KB     | ################### | 100%
jupyter_console-6.1. | 21 KB     | ################### | 100%
tensorboard-2.1.0    | 3.3 MB    | ################### | 100%
traitlets-4.3.3      | 133 KB    | ################### | 100%
pyqt-5.12.3          | 4.7 MB    | ################### | 100%
pickleshare-0.7.5    | 12 KB     | ################### | 100%
mkl-service-2.3.0    | 210 KB    | ################### | 100%
kiwisolver-1.1.0     | 61 KB     | ################### | 100%
prompt-toolkit-3.0.5 | 232 KB    | ################### | 100%
tornado-6.0.4        | 643 KB    | ################### | 100%
numpy-1.18.1         | 4.7 MB    | ################### | 100%
protobuf-3.11.4      | 583 KB    | ################### | 100%
jsonschema-3.2.0     | 108 KB    | ################### | 100%
rsa-4.0              | 27 KB     | ################### | 100%
wcwidth-0.1.9        | 20 KB     | ################### | 100%
grpcio-1.27.2        | 1.2 MB    | ################### | 100%
dask-core-2.13.0     | 596 KB    | ################### | 100%
tensorflow-estimator | 251 KB    | ################### | 100%
qtconsole-4.7.2      | 87 KB     | ################### | 100%
terminado-0.8.3      | 23 KB     | ################### | 100%
_tflow_select-2.2.0  | 3 KB      | ################### | 100%
blinker-1.4          | 13 KB     | ################### | 100%
pillow-7.0.0         | 700 KB    | ################### | 100%
cryptography-2.8     | 564 KB    | ################### | 100%
notebook-6.0.3       | 7.7 MB    | ################### | 100%
jupyter_client-6.1.2 | 74 KB     | ################### | 100%
xz-5.2.4             | 815 KB    | ################### | 100%
wrapt-1.12.1         | 45 KB     | ################### | 100%
google-auth-1.12.0   | 52 KB     | ################### | 100%
jedi-0.16.0          | 772 KB    | ################### | 100%
theano-1.0.4         | 3.7 MB    | ################### | 100%
libpng-1.6.37        | 1.4 MB    | ################### | 100%
markupsafe-1.1.1     | 28 KB     | ################### | 100%
cffi-1.14.0          | 222 KB    | ################### | 100%
chardet-3.0.4        | 189 KB    | ################### | 100%
widgetsnbextension-3 | 1.8 MB    | ################### | 100%
cachetools-3.1.1     | 11 KB     | ################### | 100%
cytoolz-0.10.1       | 336 KB    | ################### | 100%
pyasn1-modules-0.2.7 | 60 KB     | ################### | 100%
pyrsistent-0.16.0    | 91 KB     | ################### | 100%
pyjwt-1.7.1          | 17 KB     | ################### | 100%
tensorflow-2.1.0     | 4 KB      | ################### | 100%
bleach-3.1.4         | 111 KB    | ################### | 100%
click-7.1.1          | 64 KB     | ################### | 100%
pyyaml-5.3.1         | 155 KB    | ################### | 100%
pysocks-1.7.1        | 27 KB     | ################### | 100%
keras-2.3.1          | 591 KB    | ################### | 100%
entrypoints-0.3      | 12 KB     | ################### | 100%
freetype-2.10.1      | 481 KB    | ################### | 100%
pywin32-227          | 7.0 MB    | ################### | 100%
nbconvert-5.6.1      | 506 KB    | ################### | 100%
gast-0.2.2           | 10 KB     | ################### | 100%
pygpu-0.7.6          | 600 KB    | ################### | 100%
pyreadline-2.1       | 141 KB    | ################### | 100%
pycparser-2.20       | 89 KB     | ################### | 100%
mistune-0.8.4        | 53 KB     | ################### | 100%
pywavelets-1.1.1     | 4.3 MB    | ################### | 100%
zstd-1.4.4           | 1.7 MB    | ################### | 100%
pywinpty-0.5.7       | 48 KB     | ################### | 100%
google-auth-oauthlib | 18 KB     | ################### | 100%
absl-py-0.9.0        | 162 KB    | ################### | 100%
scikit-learn-0.22.2. | 6.1 MB    | ################### | 100%
importlib-metadata-1 | 42 KB     | ################### | 100%
requests-oauthlib-1. | 19 KB     | ################### | 100%
win_inet_pton-1.1.0  | 7 KB      | ################### | 100%
opt_einsum-3.2.0     | 49 KB     | ################### | 100%
requests-2.23.0      | 47 KB     | ################### | 100%
scikit-image-0.16.2  | 24.1 MB   | ################### | 100%
pyopenssl-19.1.0     | 47 KB     | ################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: | b'Enabling notebook extension jupyter-js-widgets/extension...\n      - Validating: ok\n'
done

C:\Users\andreas>set "KERAS_BACKEND="

C:\Users\andreas>python C:\Users\andreas\Miniconda3\envs\compvis\etc\keras\load_config.py  1>temp.txt

C:\Users\andreas>set /p KERAS_BACKEND= 0<temp.txt

C:\Users\andreas>del temp.txt

C:\Users\andreas>python -c "import keras"  1>nul 2>&1

C:\Users\andreas>if errorlevel 1 (
ver  1>nul
 set "KERAS_BACKEND=theano"
 python -c "import keras"  1>nul 2>&1
)

C:\Users\andreas>SET DISTUTILS_USE_SDK=1

C:\Users\andreas>SET MSSdk=1

C:\Users\andreas>SET platform=

C:\Users\andreas>IF /I [AMD64] == [amd64] set "platform=true"

C:\Users\andreas>IF /I [] == [amd64] set "platform=true"

C:\Users\andreas>if defined platform (set "VSREGKEY=HKEY_LOCAL_MACHINE\SOFTWARE\Wow6432Node\Microsoft\VisualStudio\14.0" )  ELSE (set "VSREGKEY=HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\VisualStudio\14.0" )

C:\Users\andreas>for /F "skip=2 tokens=2,*" %A in ('reg query "HKEY_LOCAL_MACHINE\SOFTWARE\Wow6432Node\Microsoft\VisualStudio\14.0" /v InstallDir') do SET "VSINSTALLDIR=%B"
ERROR: The system was unable to find the specified registry key or value.

C:\Users\andreas>if "" == "" (set "VSINSTALLDIR=" )

C:\Users\andreas>if "" == "" (
ECHO "WARNING: Did not find VS in registry or in VS140COMNTOOLS env var - your compiler may not work"
 GOTO End
)
"WARNING: Did not find VS in registry or in VS140COMNTOOLS env var - your compiler may not work"
The system cannot find the batch label specified - End

(base) C:\Users\andreas>conda activate compvis

(compvis) C:\Users\andreas>conda install -c conda-forge  tqdm
Collecting package metadata (current_repodata.json): done
Solving environment: done


==> WARNING: A newer version of conda exists. <==
  current version: 4.8.2
  latest version: 4.8.3

Please update conda by running

    $ conda update -n base -c defaults conda



## Package Plan ##

  environment location: C:\Users\andreas\Miniconda3\envs\compvis

  added / updated specs:
    - tqdm


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    certifi-2019.11.28         |   py38h32f6830_1         149 KB  conda-forge
    openssl-1.1.1e             |       hfa6e2cd_0         4.7 MB  conda-forge
    tqdm-4.44.1                |     pyh9f0ad1d_0          48 KB  conda-forge
    ------------------------------------------------------------
                                           Total:         4.9 MB

The following NEW packages will be INSTALLED:

  tqdm               conda-forge/noarch::tqdm-4.44.1-pyh9f0ad1d_0

The following packages will be UPDATED:

  certifi                         2019.11.28-py38h32f6830_0 --> 2019.11.28-py38h32f6830_1
  openssl                                 1.1.1d-hfa6e2cd_0 --> 1.1.1e-hfa6e2cd_0


Proceed ([y]/n)? y


Downloading and Extracting Packages
openssl-1.1.1e       | 4.7 MB    | ############################################################################ | 100%
tqdm-4.44.1          | 48 KB     | ############################################################################ | 100%
certifi-2019.11.28   | 149 KB    | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done

(compvis) C:\Users\andreas>conda install -c conda-forge keras
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed

CondaError: KeyboardInterrupt

Terminate batch job (Y/N)? y

(compvis) C:\Users\andreas>conda install keras
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.

CondaError: KeyboardInterrupt

Terminate batch job (Y/N)? y

(compvis) C:\Users\andreas>conda install -c anaconda keras
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
failed

UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:

Specifications:

  - keras -> python[version='>=3.5,<3.6.0a0|>=3.6,<3.7.0a0']

Your python: python=3.8

If python is on the left-most side of the chain, that's the version you've asked for.
When python appears to the right, that indicates that the thing on the left is somehow
not available for the python version you are constrained to. Note that conda will not
change your python version to a different minor version unless you explicitly specify
that.




(compvis) C:\Users\andreas>conda install -c conda-forge keras
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: \
Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
failed

UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:

Specifications:

  - keras -> python[version='2.7.*|3.5.*|3.6.*|>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|>=3.5,<3.6.0a0|3.4.*']

Your python: python=3.8

If python is on the left-most side of the chain, that's the version you've asked for.
When python appears to the right, that indicates that the thing on the left is somehow
not available for the python version you are constrained to. Note that conda will not
change your python version to a different minor version unless you explicitly specify
that.




(compvis) C:\Users\andreas>conda install python=3.6
Collecting package metadata (current_repodata.json): done
Solving environment: done


==> WARNING: A newer version of conda exists. <==
  current version: 4.8.2
  latest version: 4.8.3

Please update conda by running

    $ conda update -n base -c defaults conda



## Package Plan ##

  environment location: C:\Users\andreas\Miniconda3\envs\compvis

  added / updated specs:
    - python=3.6


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    blas-1.0                   |              mkl           6 KB
    certifi-2019.11.28         |           py36_1         157 KB
    cytoolz-0.10.1             |   py36he774522_0         303 KB
    entrypoints-0.3            |           py36_0          12 KB
    icu-58.2                   |       ha66f8fd_1         9.4 MB
    ipykernel-5.1.4            |   py36h39e3cac_0         172 KB
    ipython-7.13.0             |   py36h5ca1d4c_0        1010 KB
    jedi-0.16.0                |           py36_1         768 KB
    jsonschema-2.6.0           |   py36h7636477_0         102 KB
    jupyter_core-4.6.1         |           py36_0          86 KB
    kiwisolver-1.1.0           |   py36ha925a31_0          53 KB
    markupsafe-1.1.1           |   py36he774522_0          31 KB
    matplotlib-3.1.3           |           py36_0          22 KB
    matplotlib-base-3.1.3      |   py36h64f37c6_0         4.9 MB
    mistune-0.8.4              |   py36he774522_0          55 KB
    mkl-service-2.3.0          |   py36hb782905_0         210 KB
    mkl_fft-1.0.15             |   py36h14836fe_0         118 KB
    mkl_random-1.1.0           |   py36h675688f_0         233 KB
    nbconvert-5.6.1            |           py36_0         475 KB
    notebook-6.0.3             |           py36_0         4.3 MB
    numpy-1.18.1               |   py36h93ca92e_0           6 KB
    numpy-base-1.18.1          |   py36hc3f5095_1         3.8 MB
    openssl-1.1.1e             |       he774522_0         4.8 MB
    pickleshare-0.7.5          |           py36_0          13 KB
    pillow-7.0.0               |   py36hcc1f983_0         652 KB
    pyqt-5.9.2                 |   py36h6538335_2         3.3 MB
    python-3.6.10              |       h9f7ef89_0        15.9 MB
    pywavelets-1.1.1           |   py36he774522_0         3.4 MB
    pywin32-227                |   py36he774522_1         5.6 MB
    pywinpty-0.5.7             |           py36_0          50 KB
    pyzmq-18.1.1               |   py36ha925a31_0         399 KB
    qt-5.9.7                   |   vc14h73c81de_0        72.5 MB
    scikit-image-0.16.2        |   py36h47e9c7a_0        22.6 MB
    scikit-learn-0.22.1        |   py36h6288b17_0         4.7 MB
    scipy-1.4.1                |   py36h9439919_0        11.9 MB
    setuptools-46.1.3          |           py36_0         527 KB
    sip-4.19.8                 |   py36h6538335_0         262 KB
    six-1.14.0                 |           py36_0          27 KB
    terminado-0.8.3            |           py36_0          26 KB
    tornado-6.0.4              |   py36he774522_1         604 KB
    traitlets-4.3.3            |           py36_0         140 KB
    widgetsnbextension-3.5.1   |           py36_0         868 KB
    wincertstore-0.2           |   py36h7fe50ca_0          14 KB
    ------------------------------------------------------------
                                           Total:       174.3 MB

The following NEW packages will be INSTALLED:

  blas               pkgs/main/win-64::blas-1.0-mkl
  mkl-service        pkgs/main/win-64::mkl-service-2.3.0-py36hb782905_0
  mkl_fft            pkgs/main/win-64::mkl_fft-1.0.15-py36h14836fe_0
  mkl_random         pkgs/main/win-64::mkl_random-1.1.0-py36h675688f_0
  numpy-base         pkgs/main/win-64::numpy-base-1.18.1-py36hc3f5095_1
  sip                pkgs/main/win-64::sip-4.19.8-py36h6538335_0

The following packages will be REMOVED:

  importlib_metadata-1.5.0-py38_0
  pyrsistent-0.15.7-py38hfa6e2cd_0
  python_abi-3.8-1_cp38

The following packages will be UPDATED:

  ca-certificates    conda-forge::ca-certificates-2019.11.~ --> pkgs/main::ca-certificates-2020.1.1-0
  jedi                      conda-forge::jedi-0.16.0-py38_0 --> pkgs/main::jedi-0.16.0-py36_1
  pywin32            conda-forge::pywin32-227-py38hfa6e2cd~ --> pkgs/main::pywin32-227-py36he774522_1
  scipy              conda-forge::scipy-1.3.2-py38h582fac2~ --> pkgs/main::scipy-1.4.1-py36h9439919_0
  setuptools          conda-forge::setuptools-46.0.0-py38_0 --> pkgs/main::setuptools-46.1.3-py36_0
  tornado            conda-forge::tornado-6.0.4-py38hfa6e2~ --> pkgs/main::tornado-6.0.4-py36he774522_1

The following packages will be SUPERSEDED by a higher-priority channel:

  certifi            conda-forge::certifi-2019.11.28-py38h~ --> pkgs/main::certifi-2019.11.28-py36_1
  cytoolz            conda-forge::cytoolz-0.10.1-py38hfa6e~ --> pkgs/main::cytoolz-0.10.1-py36he774522_0
  entrypoints        conda-forge::entrypoints-0.3-py38_1000 --> pkgs/main::entrypoints-0.3-py36_0
  icu                      conda-forge::icu-64.2-he025d50_1 --> pkgs/main::icu-58.2-ha66f8fd_1
  ipykernel          conda-forge::ipykernel-5.1.4-py38h5ca~ --> pkgs/main::ipykernel-5.1.4-py36h39e3cac_0
  ipython            conda-forge::ipython-7.13.0-py38h5ca1~ --> pkgs/main::ipython-7.13.0-py36h5ca1d4c_0
  jsonschema           conda-forge::jsonschema-3.2.0-py38_0 --> pkgs/main::jsonschema-2.6.0-py36h7636477_0
  jupyter_core       conda-forge::jupyter_core-4.6.3-py38_0 --> pkgs/main::jupyter_core-4.6.1-py36_0
  kiwisolver         conda-forge::kiwisolver-1.1.0-py38he9~ --> pkgs/main::kiwisolver-1.1.0-py36ha925a31_0
  markupsafe         conda-forge::markupsafe-1.1.1-py38hfa~ --> pkgs/main::markupsafe-1.1.1-py36he774522_0
  matplotlib                conda-forge::matplotlib-3.2.0-1 --> pkgs/main::matplotlib-3.1.3-py36_0
  matplotlib-base    conda-forge::matplotlib-base-3.2.0-py~ --> pkgs/main::matplotlib-base-3.1.3-py36h64f37c6_0
  mistune            conda-forge::mistune-0.8.4-py38hfa6e2~ --> pkgs/main::mistune-0.8.4-py36he774522_0
  nbconvert             conda-forge::nbconvert-5.6.1-py38_0 --> pkgs/main::nbconvert-5.6.1-py36_0
  notebook               conda-forge::notebook-6.0.3-py38_0 --> pkgs/main::notebook-6.0.3-py36_0
  numpy              conda-forge::numpy-1.18.1-py38hc71023~ --> pkgs/main::numpy-1.18.1-py36h93ca92e_0
  openssl            conda-forge::openssl-1.1.1e-hfa6e2cd_0 --> pkgs/main::openssl-1.1.1e-he774522_0
  pickleshare        conda-forge::pickleshare-0.7.5-py38_1~ --> pkgs/main::pickleshare-0.7.5-py36_0
  pillow             conda-forge::pillow-7.0.0-py38h9ea1dd~ --> pkgs/main::pillow-7.0.0-py36hcc1f983_0
  pyqt               conda-forge::pyqt-5.12.3-py38h6538335~ --> pkgs/main::pyqt-5.9.2-py36h6538335_2
  python             conda-forge::python-3.8.2-h5fd99cc_4_~ --> pkgs/main::python-3.6.10-h9f7ef89_0
  pywavelets         conda-forge::pywavelets-1.1.1-py38hc8~ --> pkgs/main::pywavelets-1.1.1-py36he774522_0
  pywinpty               conda-forge::pywinpty-0.5.7-py38_0 --> pkgs/main::pywinpty-0.5.7-py36_0
  pyzmq              conda-forge::pyzmq-19.0.0-py38h16f901~ --> pkgs/main::pyzmq-18.1.1-py36ha925a31_0
  qt                      conda-forge::qt-5.12.5-h7ef1ec2_0 --> pkgs/main::qt-5.9.7-vc14h73c81de_0
  scikit-image       conda-forge::scikit-image-0.16.2-py38~ --> pkgs/main::scikit-image-0.16.2-py36h47e9c7a_0
  scikit-learn       conda-forge::scikit-learn-0.22.2.post~ --> pkgs/main::scikit-learn-0.22.1-py36h6288b17_0
  six                        conda-forge::six-1.14.0-py38_0 --> pkgs/main::six-1.14.0-py36_0
  terminado             conda-forge::terminado-0.8.3-py38_0 --> pkgs/main::terminado-0.8.3-py36_0
  traitlets             conda-forge::traitlets-4.3.3-py38_0 --> pkgs/main::traitlets-4.3.3-py36_0
  widgetsnbextension conda-forge::widgetsnbextension-3.5.1~ --> pkgs/main::widgetsnbextension-3.5.1-py36_0
  wincertstore       conda-forge::wincertstore-0.2-py38_10~ --> pkgs/main::wincertstore-0.2-py36h7fe50ca_0


Proceed ([y]/n)? y


Downloading and Extracting Packages
ipykernel-5.1.4      | 172 KB    | ############################################################################ | 100%
numpy-base-1.18.1    | 3.8 MB    | ############################################################################ | 100%
scikit-image-0.16.2  | 22.6 MB   | ############################################################################ | 100%
widgetsnbextension-3 | 868 KB    | ############################################################################ | 100%
pyqt-5.9.2           | 3.3 MB    | ############################################################################ | 100%
jedi-0.16.0          | 768 KB    | ############################################################################ | 100%
scipy-1.4.1          | 11.9 MB   | ############################################################################ | 100%
matplotlib-base-3.1. | 4.9 MB    | ############################################################################ | 100%
pickleshare-0.7.5    | 13 KB     | ############################################################################ | 100%
blas-1.0             | 6 KB      | ############################################################################ | 100%
kiwisolver-1.1.0     | 53 KB     | ############################################################################ | 100%
six-1.14.0           | 27 KB     | ############################################################################ | 100%
mkl-service-2.3.0    | 210 KB    | ############################################################################ | 100%
scikit-learn-0.22.1  | 4.7 MB    | ############################################################################ | 100%
entrypoints-0.3      | 12 KB     | ############################################################################ | 100%
pywavelets-1.1.1     | 3.4 MB    | ############################################################################ | 100%
certifi-2019.11.28   | 157 KB    | ############################################################################ | 100%
openssl-1.1.1e       | 4.8 MB    | ############################################################################ | 100%
wincertstore-0.2     | 14 KB     | ############################################################################ | 100%
pyzmq-18.1.1         | 399 KB    | ############################################################################ | 100%
pywinpty-0.5.7       | 50 KB     | ############################################################################ | 100%
pywin32-227          | 5.6 MB    | ############################################################################ | 100%
mkl_fft-1.0.15       | 118 KB    | ############################################################################ | 100%
terminado-0.8.3      | 26 KB     | ############################################################################ | 100%
python-3.6.10        | 15.9 MB   | ############################################################################ | 100%
jsonschema-2.6.0     | 102 KB    | ############################################################################ | 100%
notebook-6.0.3       | 4.3 MB    | ############################################################################ | 100%
jupyter_core-4.6.1   | 86 KB     | ############################################################################ | 100%
cytoolz-0.10.1       | 303 KB    | ############################################################################ | 100%
mistune-0.8.4        | 55 KB     | ############################################################################ | 100%
sip-4.19.8           | 262 KB    | ############################################################################ | 100%
mkl_random-1.1.0     | 233 KB    | ############################################################################ | 100%
icu-58.2             | 9.4 MB    | ############################################################################ | 100%
numpy-1.18.1         | 6 KB      | ############################################################################ | 100%
setuptools-46.1.3    | 527 KB    | ############################################################################ | 100%
matplotlib-3.1.3     | 22 KB     | ############################################################################ | 100%
markupsafe-1.1.1     | 31 KB     | ############################################################################ | 100%
traitlets-4.3.3      | 140 KB    | ############################################################################ | 100%
tornado-6.0.4        | 604 KB    | ############################################################################ | 100%
nbconvert-5.6.1      | 475 KB    | ############################################################################ | 100%
ipython-7.13.0       | 1010 KB   | ############################################################################ | 100%
qt-5.9.7             | 72.5 MB   | ############################################################################ | 100%
pillow-7.0.0         | 652 KB    | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: / b'Uninstalling jupyter-js-widgets jupyter-js-widgets/extension\nRemoving: C:\\Users\\andreas\\Miniconda3\\envs\\compvis\\share\\jupyter\\nbextensions\\jupyter-js-widgets\n'
/ WARNING conda.gateways.disk.delete:unlink_or_rename_to_trash(140): Could not remove or rename C:\Users\andreas\Miniconda3\envs\compvis\Lib\site-packages\matplotlib\mpl-data\fonts\ttf\DejaVuSans.ttf.  Please remove this file manually (you may need to reboot to free file handles)
| DEBUG menuinst_win32:__init__(199): Menu: name: 'Anaconda${PY_VER} ${PLATFORM}', prefix: 'C:\Users\andreas\Miniconda3\envs\compvis', env_name: 'compvis', mode: 'user', used_mode: 'user'
DEBUG menuinst_win32:create(323): Shortcut cmd is C:\Users\andreas\Miniconda3\python.exe, args are ['C:\\Users\\andreas\\Miniconda3\\cwp.py', 'C:\\Users\\andreas\\Miniconda3\\envs\\compvis', 'C:\\Users\\andreas\\Miniconda3\\envs\\compvis\\python.exe', 'C:\\Users\\andreas\\Miniconda3\\envs\\compvis\\Scripts\\jupyter-notebook-script.py', '"%USERPROFILE%/"']
done

(compvis) C:\Users\andreas>
(compvis) C:\Users\andreas>
(compvis) C:\Users\andreas>conda install python=3.6
Collecting package metadata (current_repodata.json): done
Solving environment: done


==> WARNING: A newer version of conda exists. <==
  current version: 4.8.2
  latest version: 4.8.3

Please update conda by running

    $ conda update -n base -c defaults conda



# All requested packages already installed.


(compvis) C:\Users\andreas>conda update -n base -c defaults conda
Collecting package metadata (current_repodata.json): done
Solving environment: done

## Package Plan ##

  environment location: C:\Users\andreas\Miniconda3

  added / updated specs:
    - conda


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    certifi-2019.11.28         |           py37_1         157 KB
    conda-4.8.3                |           py37_0         2.8 MB
    idna-2.9                   |             py_1          49 KB
    pycparser-2.20             |             py_0          92 KB
    requests-2.23.0            |           py37_0          93 KB
    setuptools-46.1.3          |           py37_0         528 KB
    tqdm-4.44.1                |             py_0          57 KB
    ------------------------------------------------------------
                                           Total:         3.8 MB

The following packages will be UPDATED:

  certifi                                 2019.11.28-py37_0 --> 2019.11.28-py37_1
  conda                                        4.8.2-py37_0 --> 4.8.3-py37_0
  idna                    pkgs/main/win-64::idna-2.8-py37_0 --> pkgs/main/noarch::idna-2.9-py_1
  openssl                                 1.1.1d-he774522_4 --> 1.1.1e-he774522_0
  pycparser          pkgs/main/win-64::pycparser-2.19-py37~ --> pkgs/main/noarch::pycparser-2.20-py_0
  requests                                    2.22.0-py37_1 --> 2.23.0-py37_0
  setuptools                                  45.2.0-py37_0 --> 46.1.3-py37_0
  tqdm                                          4.42.1-py_0 --> 4.44.1-py_0


Proceed ([y]/n)? y


Downloading and Extracting Packages
setuptools-46.1.3    | 528 KB    | ############################################################################ | 100%
idna-2.9             | 49 KB     | ############################################################################ | 100%
requests-2.23.0      | 93 KB     | ############################################################################ | 100%
tqdm-4.44.1          | 57 KB     | ############################################################################ | 100%
pycparser-2.20       | 92 KB     | ############################################################################ | 100%
conda-4.8.3          | 2.8 MB    | ############################################################################ | 100%
certifi-2019.11.28   | 157 KB    | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done

(compvis) C:\Users\andreas>conda install python=3.6
Collecting package metadata (current_repodata.json): done
Solving environment: done

# All requested packages already installed.


(compvis) C:\Users\andreas>conda install -c conda-forge keras
Collecting package metadata (current_repodata.json): done
Solving environment: done

## Package Plan ##

  environment location: C:\Users\andreas\Miniconda3\envs\compvis

  added / updated specs:
    - keras


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    absl-py-0.9.0              |   py36h9f0ad1d_1         162 KB  conda-forge
    astor-0.7.1                |             py_0          22 KB  conda-forge
    certifi-2019.11.28         |   py36h9f0ad1d_1         149 KB  conda-forge
    gast-0.3.3                 |             py_0          12 KB  conda-forge
    grpcio-1.23.0              |   py36hc6b9980_1         1.0 MB  conda-forge
    h5py-2.10.0                |nompi_py36h422b98e_102         936 KB  conda-forge
    hdf5-1.10.5                |nompi_ha405e13_1104        35.1 MB  conda-forge
    keras-2.3.1                |   py36h21ff451_0         589 KB  conda-forge
    keras-applications-1.0.8   |             py_1          30 KB  conda-forge
    keras-preprocessing-1.1.0  |             py_0          33 KB  conda-forge
    libgpuarray-0.7.6          |    hfa6e2cd_1003         314 KB  conda-forge
    libprotobuf-3.11.4         |       h1a1b453_0         2.2 MB  conda-forge
    mako-1.1.0                 |             py_0          57 KB  conda-forge
    markdown-3.2.1             |             py_0          61 KB  conda-forge
    protobuf-3.11.4            |   py36he025d50_0         583 KB  conda-forge
    pygpu-0.7.6                |py36hc8d92b1_1000         594 KB  conda-forge
    pyreadline-2.1             |        py36_1001         141 KB  conda-forge
    python_abi-3.6             |          1_cp36m           4 KB  conda-forge
    pyyaml-5.3.1               |   py36h68a101e_0         155 KB  conda-forge
    tensorboard-1.13.1         |           py36_0         3.3 MB  conda-forge
    tensorflow-1.13.2          |       h21ff451_0          22 KB  conda-forge
    tensorflow-base-1.13.2     |           py36_0        52.5 MB  conda-forge
    tensorflow-estimator-1.13.0|   py36h39e3cac_0         475 KB  conda-forge
    termcolor-1.1.0            |             py_2           6 KB  conda-forge
    theano-1.0.4               |py36h6538335_1001         3.7 MB  conda-forge
    vs2015_win-64-14.0.25420   |      h55c1224_11           7 KB
    werkzeug-1.0.0             |             py_0         238 KB  conda-forge
    yaml-0.2.2                 |       hfa6e2cd_1          63 KB  conda-forge
    ------------------------------------------------------------
                                           Total:       102.4 MB

The following NEW packages will be INSTALLED:

  absl-py            conda-forge/win-64::absl-py-0.9.0-py36h9f0ad1d_1
  astor              conda-forge/noarch::astor-0.7.1-py_0
  gast               conda-forge/noarch::gast-0.3.3-py_0
  grpcio             conda-forge/win-64::grpcio-1.23.0-py36hc6b9980_1
  h5py               conda-forge/win-64::h5py-2.10.0-nompi_py36h422b98e_102
  hdf5               conda-forge/win-64::hdf5-1.10.5-nompi_ha405e13_1104
  keras              conda-forge/win-64::keras-2.3.1-py36h21ff451_0
  keras-applications conda-forge/noarch::keras-applications-1.0.8-py_1
  keras-preprocessi~ conda-forge/noarch::keras-preprocessing-1.1.0-py_0
  libgpuarray        conda-forge/win-64::libgpuarray-0.7.6-hfa6e2cd_1003
  libprotobuf        conda-forge/win-64::libprotobuf-3.11.4-h1a1b453_0
  mako               conda-forge/noarch::mako-1.1.0-py_0
  markdown           conda-forge/noarch::markdown-3.2.1-py_0
  protobuf           conda-forge/win-64::protobuf-3.11.4-py36he025d50_0
  pygpu              conda-forge/win-64::pygpu-0.7.6-py36hc8d92b1_1000
  pyreadline         conda-forge/win-64::pyreadline-2.1-py36_1001
  python_abi         conda-forge/win-64::python_abi-3.6-1_cp36m
  pyyaml             conda-forge/win-64::pyyaml-5.3.1-py36h68a101e_0
  tensorboard        conda-forge/win-64::tensorboard-1.13.1-py36_0
  tensorflow         conda-forge/win-64::tensorflow-1.13.2-h21ff451_0
  tensorflow-base    conda-forge/win-64::tensorflow-base-1.13.2-py36_0
  tensorflow-estima~ conda-forge/win-64::tensorflow-estimator-1.13.0-py36h39e3cac_0
  termcolor          conda-forge/noarch::termcolor-1.1.0-py_2
  theano             conda-forge/win-64::theano-1.0.4-py36h6538335_1001
  vs2015_win-64      pkgs/main/win-64::vs2015_win-64-14.0.25420-h55c1224_11
  werkzeug           conda-forge/noarch::werkzeug-1.0.0-py_0
  yaml               conda-forge/win-64::yaml-0.2.2-hfa6e2cd_1

The following packages will be SUPERSEDED by a higher-priority channel:

  ca-certificates     pkgs/main::ca-certificates-2020.1.1-0 --> conda-forge::ca-certificates-2019.11.28-hecc5488_0
  certifi              pkgs/main::certifi-2019.11.28-py36_1 --> conda-forge::certifi-2019.11.28-py36h9f0ad1d_1
  openssl              pkgs/main::openssl-1.1.1e-he774522_0 --> conda-forge::openssl-1.1.1e-hfa6e2cd_0


Proceed ([y]/n)? y


Downloading and Extracting Packages
gast-0.3.3           | 12 KB     | ############################################################################ | 100%
grpcio-1.23.0        | 1.0 MB    | ############################################################################ | 100%
keras-preprocessing- | 33 KB     | ############################################################################ | 100%
absl-py-0.9.0        | 162 KB    | ############################################################################ | 100%
pyyaml-5.3.1         | 155 KB    | ############################################################################ | 100%
pygpu-0.7.6          | 594 KB    | ############################################################################ | 100%
libgpuarray-0.7.6    | 314 KB    | ############################################################################ | 100%
keras-2.3.1          | 589 KB    | ############################################################################ | 100%
python_abi-3.6       | 4 KB      | ############################################################################ | 100%
werkzeug-1.0.0       | 238 KB    | ############################################################################ | 100%
hdf5-1.10.5          | 35.1 MB   | ############################################################################ | 100%
protobuf-3.11.4      | 583 KB    | ############################################################################ | 100%
keras-applications-1 | 30 KB     | ############################################################################ | 100%
tensorflow-1.13.2    | 22 KB     | ############################################################################ | 100%
mako-1.1.0           | 57 KB     | ############################################################################ | 100%
tensorflow-estimator | 475 KB    | ############################################################################ | 100%
yaml-0.2.2           | 63 KB     | ############################################################################ | 100%
astor-0.7.1          | 22 KB     | ############################################################################ | 100%
tensorflow-base-1.13 | 52.5 MB   | ############################################################################ | 100%
theano-1.0.4         | 3.7 MB    | ############################################################################ | 100%
tensorboard-1.13.1   | 3.3 MB    | ############################################################################ | 100%
h5py-2.10.0          | 936 KB    | ############################################################################ | 100%
vs2015_win-64-14.0.2 | 7 KB      | ############################################################################ | 100%
markdown-3.2.1       | 61 KB     | ############################################################################ | 100%
certifi-2019.11.28   | 149 KB    | ############################################################################ | 100%
pyreadline-2.1       | 141 KB    | ############################################################################ | 100%
termcolor-1.1.0      | 6 KB      | ############################################################################ | 100%
libprotobuf-3.11.4   | 2.2 MB    | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done

C:\Users\andreas>set "KERAS_BACKEND="

C:\Users\andreas>python C:\Users\andreas\Miniconda3\envs\compvis\etc\keras\load_config.py  1>temp.txt

C:\Users\andreas>set /p KERAS_BACKEND= 0<temp.txt

C:\Users\andreas>del temp.txt

C:\Users\andreas>python -c "import keras"  1>nul 2>&1

C:\Users\andreas>if errorlevel 1 (
ver  1>nul
 set "KERAS_BACKEND=theano"
 python -c "import keras"  1>nul 2>&1
)

C:\Users\andreas>SET DISTUTILS_USE_SDK=1

C:\Users\andreas>SET MSSdk=1

C:\Users\andreas>SET platform=

C:\Users\andreas>IF /I [AMD64] == [amd64] set "platform=true"

C:\Users\andreas>IF /I [] == [amd64] set "platform=true"

C:\Users\andreas>if defined platform (set "VSREGKEY=HKEY_LOCAL_MACHINE\SOFTWARE\Wow6432Node\Microsoft\VisualStudio\14.0" )  ELSE (set "VSREGKEY=HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\VisualStudio\14.0" )

C:\Users\andreas>for /F "skip=2 tokens=2,*" %A in ('reg query "HKEY_LOCAL_MACHINE\SOFTWARE\Wow6432Node\Microsoft\VisualStudio\14.0" /v InstallDir') do SET "VSINSTALLDIR=%B"
ERROR: The system was unable to find the specified registry key or value.

C:\Users\andreas>if "" == "" (set "VSINSTALLDIR=" )

C:\Users\andreas>if "" == "" (
ECHO "WARNING: Did not find VS in registry or in VS140COMNTOOLS env var - your compiler may not work"
 GOTO End
)
"WARNING: Did not find VS in registry or in VS140COMNTOOLS env var - your compiler may not work"
The system cannot find the batch label specified - End

(compvis) C:\Users\andreas>
(compvis) C:\Users\andreas>
(compvis) C:\Users\andreas>file
'file' is not recognized as an internal or external command,
operable program or batch file.

(compvis) C:\Users\andreas>conda install python=3.8
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: /

CALL "%VSINSTALLDIR%VC\vcvarsall.bat" amd64 

perlintro – a brief introduction and overview of Perl
perlop – Perl operators and precedence
perlobj – Perl object reference
perldebug – Perl debugging
perlrequick – Perl regular expressions quick start

Perl Environment Include/Library Path

# perl -e "print qq(@INC)"
/usr/local/lib/perl5/site_perl/mach/5.20 /usr/local/lib/perl5/site_perl /usr/local/lib/perl5/5.20/mach /usr/local/lib/perl5/5.20 /usr/local/lib/perl5/site_perl/5.20 /usr/local/lib/perl5/site_perl/5.20/mach

# find /usr/local/lib/perl5 -name "*.pm"
/usr/local/lib/perl5/5.20/AnyDBM_File.pm
/usr/local/lib/perl5/5.20/App/Cpan.pm
...

Variable Type

Perl – Variables

Enum

Does Perl have an enumeration type?

RegEx

Regular Expressions and Matching
perl – strings comparison and regex

System Command-Line

perldoc: system
How can I store the result of a system command in a Perl variable?
How can I capture STDERR from an external command?

Name of the Perl script

How to get the name of Perl script that is running

print $0;

Command Line Arguments

• Use $ARGV[n] to display argument.
• Use $#ARGV to get total number of passed argument to a perl script.

Processing command line arguments – @ARGV in Perl
Perl Display And Pass Command Line Arguments With @argv
How to read Perl command-line arguments

my $argc= $#ARGV + 1;

my $name   = $ARGV[0];
my $number = $ARGV[1];
# or
my ($name, $number) = @ARGV;

Loops (for, foreach, etc.)

Perl for loop explained with examples

defined

perldoc: defined

Arrays

Perl Arrays

Note, when accessing a single element of an array the leading sigil changes from @ to $. This might cause confusion to some people, but if you think about it, it is quite obvious why.

@ marks plural and $ marks singular. When accessing a single element of an array it behaves just as a regular scalar variable.

# Declare an array
my @names;

# Declare and assign values:
my @names = ("Foo", "Bar", "Baz");

# Debugging of an array
use Data::Dumper qw(Dumper);
my @names = ("Foo", "Bar", "Baz");
say Dumper \@names;
# $VAR1 = [
#         'Foo',
#         'Bar',
#         'Baz'
#       ];

# foreach loop and perl arrays
my @names = ("Foo", "Bar", "Baz");
foreach my $n (@names) {
  say $n;
}
# Foo
# Bar
# Baz

# Accessing an element of an array
my @names = ("Foo", "Bar", "Baz");
say $names[0];

Indexing array

The indexes of an array start from 0. The largest index is always in the variable called $#name_of_the_array. So

my @names = ("Foo", "Bar", "Baz");
say $#names;

Will print 2 because the indexes are 0,1 and 2.

Length or size of an array

In Perl there is no special function to fetch the size of an array, but there are several ways to obtain that value. For one, the size of the array is one more than the largest index. In the above case $#names+1 is the size or length of the array.

In addition the scalar function can be used to to obtain the size of an array:

my @names = ("Foo", "Bar", "Baz");
say scalar @names;

Will print 3.

The scalar function is sort of a casting function that – among other things – converts an array to a scalar. Due to an arbitrary, but clever decision this conversion yields the size of the array.

Loop on the indexes of an array

There are cases when looping over the values of an array is not enough. We might need both the value and the index of that value. In that case we need to loop over the indexes, and obtain the values using the indexes:

my @names = ("Foo", "Bar", "Baz");
foreach my $i (0 .. $#names) {
  say "$i - $names[$i]";
}

prints:

0 - Foo
1 - Bar
2 - Baz

String

Perl string concatenation – How to concatenate strings with Perl

• Perl string concatenation – Method #1 – Using ${name}
• Perl string concatenation – Method #2 – using Perl’s dot operator
• Perl string concatenation – Method #3 – using Perl’s join function

$name = 'foo';
$filename = "/tmp/${name}.tmp";

$name = checkbook'; 
$filename = '/tmp/' . $name . '.tmp'; 
# $filename now contains "/tmp/checkbook.tmp"

$name = 'checkbook'; 
$filename = join '', '/tmp/', $name, '.tmp'; 
# $filename now contains "/tmp/checkbook.tmp"

File I/O

How to tell perl to print to a file handle instead of printing the file handle? !!!

Writing to files with Perl
Perl – File I/O
How to remove one line from a file using Perl?
How do I delete a certain line from a file with Perl?
Insert a line at the beginning of a file

• "<file.txt": read-only mode
• ">file.txt": writing mode
• "+<file.txt": updating without truncating
• "+>file.txt": truncate the file first
• ">>file.txt": append mode
• "+>>file.txt": append mode with read

use strict;
use warnings;
 
my $filename = 'report.txt';
open(my $fh, '>', $filename) or die "Could not open file '$filename' $!";
print $fh "My first report generated by perl\n";
close $fh;
print "done\n";

Process List

Day 17: Checking process existence and listing processes (Proc::Find)
ps in perl?
Proc::Find – Find processes by name, PID, or some other attributes
Proc::ProcessTable – Perl extension to access the unix process table

# perl ...
Can't locate Proc/Find.pm in @INC (you may need to install the Proc::Find module)

Perl 6

Tutorials / Types in Perl 6 / Enums

svnweb.freebsd.org/base/release/10.2.0/bin/pkill/
Tracker, is a filesystem indexer, metadata storage system and search tool.
fossies.org/linux/tracker/src/tracker/tracker-process.c

How can a process inquire, when it was started?
github.com/dnabre/misc/tree/master/proc_info, Get time process started
github.com/hishamhm/htop/blob/master/freebsd/FreeBSDProcessList.c

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>

#include <signal.h>

/* _POSIX2_LINE_MAX */
#include <limits.h>

/* kvm_openfiles(), kvm_getprocs() */
#include <kvm.h>

/* errx() */
#include <err.h>

/* _PATH_DEVNULL */
#include <paths.h>

/* O_RDONLY */
#include <fcntl.h>

/* KERN_PROC_PROC */
#include <sys/sysctl.h>

/* struct kinfo_proc */
#include <sys/user.h>

#define STATUS_MATCH    0
#define STATUS_NOMATCH  1
#define STATUS_BADUSAGE 2
#define STATUS_ERROR    3

int
main(int argc, char **argv)
{
    int i;

    /* PID */
    pid_t mypid;
    pid_t pid;

    /* KVM openfiles() */
    kvm_t      *kd;
    const char *execf;
    const char *coref;
    char        buf[_POSIX2_LINE_MAX];

    /* KVM getprocs() */
    int                 nproc;
    struct kinfo_proc  *plist;
    struct kinfo_proc  *kp;

    /* KVM getargv() */
    char **strv;

    char *selected;

    execf = NULL;
    coref = _PATH_DEVNULL;

    mypid = getpid();

    /*
     * Retrieve the list of running processes from the kernel.
     */
    kd = kvm_openfiles(execf, coref, NULL, O_RDONLY, buf);
    if (kd == NULL)
        errx(STATUS_ERROR, "Cannot open kernel files (%s)", buf);

    /*
     * Use KERN_PROC_PROC instead of KERN_PROC_ALL, since we
     * just want processes and not individual kernel threads.
     */
    plist = kvm_getprocs(kd, KERN_PROC_PROC, 0, &nproc);
    if (plist == NULL) {
        errx(STATUS_ERROR, "Cannot get process list (%s)",
            kvm_geterr(kd));
    }
    printf("nproc=%d\n", nproc);

    /*
     * Allocate memory which will be used to keep track of the
     * selection.
     */
    if ((selected = malloc(nproc)) == NULL) {
        err(STATUS_ERROR, "Cannot allocate memory for %d processes",
            nproc);
    }
    memset(selected, 0, nproc);

    /*
     * Take the appropriate action for each matched process, if any.
     */
    for (i = 0, kp = plist; i < nproc; i++, kp++) {
        printf("comm=%s tdname=%s wmesg=%s login=%s lockname=%s emul=%s loginclass=%s",
            kp->ki_comm,
            kp->ki_tdname,
            kp->ki_wmesg,
            kp->ki_login,
            kp->ki_lockname,
            kp->ki_emul,
            kp->ki_loginclass);
        if ((strv = kvm_getargv(kd, kp, 0)) != NULL) {
            printf(" argv=%s", strv[0]);
        }
        printf("\n");
    }

    return 0;
}

There are four major ML models:

Supervised Machine Learning Algorithms

• Linear Regression
• Logistic Regression
• Random Forest
• Gradient Boosted Trees
• Support Vector Machines (SVM)
• Neural Networks
• Decision Trees
• Naive Bayes
• Nearest Neighbor

Semi-supervised Machine Learning Algorithms

• Unsupervised Machine Learning Algorithms
• k-means clustering
• t-SNE (t-Distributed Stochastic Neighbor Embedding)
• PCA (Principal Component Analysis)
• Association rule

Reinforcement Machine Learning Algorithms

• Q-Learning
• Temporal Difference (TD)
• Monte-Carlo Tree Search (MCTS)
• Asynchronous Actor-Critic Agents (A3C)

• Qualitätssicherung
• Risikobeurteilung
• Qualitätsmanagement
• ISO 9001

ISO 26’000

ISO 26000
Was ist ISO 26000 – Kurz und kompakt erklärt
Corporate Social Responsibility (CSR): Praktische Perspektiven von Thomas Beschorner
Was ist eigentlich Corporate Social Responsibility (CSR)?
Little Green Bags: Was ist echte unternehmerische Nachhaltigkeit?

Demingkreis

EFQM – Das Kriterienmodell (Playlist)
Total Quality Management (TQM & EFQM) einfach erklärt – Qualitätsmanagement in Unternehmen
Frag den Prof: Change Management
Change Management – Brokkoli: Change Management einfach erklärt

Florian Frankl

QM-System für Einsteiger
Qualitätsmanagement

audit hilfe

ISO 9001
15 Pflichtelemente einer Managementbewertung nach ISO 9001

Schütte Quality Solutions

ISO 9001 Qualitätsmanagement

VOREST AG

Qualitätsmanagement – QM ISO 9001
Qualitätssicherung & Methoden
Prozessmanagement
Umweltmanagement ISO 14001 & Umweltschutz

MariusEbert

TQM und EFQM, 14.12.2019
Qualitätsprüfung, Fragen, 12.12.2019
Qualitätsanforderungen der Kunden, 11.12.2019
Qualitätsmanagement, Argumente dafür, Mind Map, 09.09.2019
Lieferantenbezogene Qualitätssicherung, wie?, 18.05.2018
Qualitätsaudit, Bestandteile, 01.04.2015
Instandhaltung u. Qualitätsmanagement, Zusammenhang, 25.03.2015
Qualitätslenkung in der Fertigung, Funktion, 25.03.2015
Ishikawa-Diagramm und Qualitätsmanagement, 09.03.2015
TQM, Maßnahmen, 09.03.2015
TQM, Grundgedanke u. Philosophie, 09.03.2015
QFD, Erfassung u. Umsetzung der Kundenwünsche, 07.03.2015
Qualitätsanforderungen des Kunden
Qualitätsprüfung, welche grundlegenden Fragen?
Magisches Qualitätsdreieck, Begriff
Total Quality Management (TQM), 22.09.2010
TQM und EFQM, 14.12.2019
Total Quality Management (TQM), Merkmale, Prüfungsfrage, 14.06.2012
Total Quality Management (TQM), Grundgedanke
ISO 9001, Regelkreis
Konzept zur Qualitätssicherung, 01.08.2012
Lean Management
Total Quality Management (TQM), 30.09.2011
Total Quality Management (TQM) und Kunde, 30.09.2011
Qualitätsmanagement Marius Ebert (Playlist)

Woche 9

Bow-Tie-Analyse
Ursache-Wirkungs-Diagramm, Ishikawa-Diagramm, Fishbone-Diagramm
FMEA (Failure Mode and Effects Analysis)
PAAG-Verfahren, wie HAZOP-Verfahren (von englisch Hazard and Operability)
Hazard and Operability Study (HAZOP)

• FMEA
• HAZOP
• Ishikawa
• Fishbone
• Fault Tree Analysis

Articles

Do companies get the most out of Hazard & Operability (HazOp) analysis?

YouTube

Ishikawa Diagramm Erklärung & Beispiel (Unternehmensführung Fachwirt IHK) -Fischgrätendiagramm
Wie funktioniert das Ishikawa Diagramm? – Ishikawa Beispiel & Erklärung

Woche 10

Fehlerbaumanalyse, Fault Tree Analysis (FTA)

YouTube

Erklärvideo: Risikomanagement 2.0
Folge 14 – Risiken im Projekt managen (Teil 1)
Risikomanagement, Teil 1: Risikopolitik

Woche 15

Developing Effective Bow Tie Diagrams Webinar, ABBConsultingUK
Learning with Risktec

Risk Reduction & ALARP (for High Hazard Industries), 16.01.2019
Risk & Safety Management: Making Training Count with ALARP, Bowtie and more, 21.08.2018

Does risk assessment reveal risk?
Finding things to worry about
Why investigate – part 1
Why investigate – Part 2
Risk Acceptance 1 – Introduction
Risk Acceptance 2 – Absolute risk
Risk Acceptance 3 – Relative risk
Risk Acceptance 4 – Trade-offs
Risk Acceptance 5 – ALARP
Risk Acceptance 6 – Implied Acceptability
Risk Acceptance 7 – Fiat
What is safety

Risikobeurteilung (Playlist)

Wie denke ich strategisch? Strategie als Sehen nach Mintzberg
Management & Unternehmensführung | Operative & Strategische Unternehmensführung | BWL
Einführung in effektives und effizientes Risikomanagement nach DIN ISO 31000

Mathematik

Measuring Reliability
08 Exponentialverteilungen Einführung
09 Exponentialverteilungen Definition und Dichtefunktion
Zufallsvariable, Massenfunktion, Dichtefunktion und Verteilungsfunktion
Dichtefunktion: Wie rechnet man damit? Wie zeichnet man eine Dichte? Was sind die Eigenschaften?
Rechnen mit einer Dichtefunktion: Erwartungswert, Median, Verteilungsfunktion bestimmen
4.5.7 Mean Time to Failure: Video

Naive Bayes Classifier

Naive Bayes Classifier

• IAML5.1: Overview
• IAML5.2: Bayesian classification
• IAML5.3: Class model and the prior
• IAML5.4: Role of denominator in Naive Bayes
• IAML5.5: Probabilistic classifiers: generative vs discriminative
• IAML5.6: Independence assumption in Naive Bayes
• IAML5.7: Mutual independence vs conditional independence
• IAML5.8: Naive Bayes for real-valued data
• IAML5.9: Gaussian Naive Bayes classifier
• IAML5.10: Naive Bayes decision boundary
• IAML5.11: Example where Naive Bayes fails
• IAML5.12: Naive Bayes for spam detection
• IAML5.13: The zero-frequency problem
• IAML5.14: Missing values in Naive Bayes

Decision Tree Learning

Decision Tree Learning

• IAML7.1 Decision Trees: an introduction
• IAML7.2 Decision tree example
• IAML7.3 Quinlan’s ID3 algorithm
• IAML7.4 Decision tree: split purity
• IAML7.5 Decision tree entropy
• IAML7.6 Information gain
• IAML7.7 Overfitting in decision trees
• IAML7.8 Decision tree pruning
• IAML7.9 Information gain ratio
• IAML7.10 Decision trees are DNF formulas
• IAML7.11 Decision trees and real-valued data
• IAML7.12 Decision tree regression
• IAML7.13 Pros and cons of decision trees
• IAML7.14 Random forest algorithm
• IAML7.15 Summary

Generalization and Evaluation

Generalization and Evaluation

• IAML8.1 Generalization in machine learning
• IAML8.2 Overfitting and underfitting
• IAML8.3 Examples of overfitting and underfitting
• IAML8.4 How to control overfitting
• IAML8.5 Generalization error
• IAML8.6 Estimating the generalization error
• IAML8.7 Confidence interval for generalization
• IAML8.8 Why we need validation sets
• IAML8.9 Cross-validation
• IAML8.10 Leave-one-out cross-validation
• IAML8.11 Stratified sampling
• IAML8.12 Evaluating classification and regression
• IAML8.13 False positives and false negatives
• IAML8.14 Classification error and accuracy
• IAML8.15 When classification error is wrong
• IAML8.16 Recall, precision, miss and false alarm
• IAML8.17 Classification cost and utility
• IAML8.18 Receiver Operating Characteristic (ROC) curve
• IAML8.19 Evaluating regression: MSE, MAE, CC
• IAML8.20 Mean squared error and outliers
• IAML8.21 Mean absolute error (MAE)
• IAML8.22 Correlation coefficient

k-Nearest Neighbor Algorithm

k-Nearest Neighbor Algorithm

• kNN.1 Overview
• kNN.2 Intuition for the nearest-neighbor method
• kNN.3 Voronoi cells and decision boundary
• kNN.4 Sensitivity to outliers
• kNN.5 Nearest-neighbor classification algorithm
• kNN.6 MNIST digit recognition
• kNN.7 Nearest-neighbor regression algorithm
• kNN.8 Nearest-neighbor regression example
• kNN.9 Number of nearest neighbors to use
• kNN.10 Similarity / distance measures
• kNN.11 Breaking ties between nearest neighbors
• kNN.12 Parzen windows, kernels and SVM
• kNN.13 Pros and cons of nearest-neighbor methods
• kNN.14 Computational complexity of finding nearest-neighbors
• kNN.15 K-d tree algorithm
• kNN.16 Locality sensitive hashing (LSH)
• kNN.17 Inverted index

K-means Clustering

K-means Clustering

• Clustering 1: monothetic vs. polythetic
• Clustering 2: soft vs. hard clustering
• Clustering 3: overview of methods
• Clustering 4: K-means clustering: how it works
• Clustering 5: K-means objective and convergence
• Clustering 6: how many clusters?
• Clustering 7: intrinsic vs. extrinsic evaluation
• Clustering 8: alignment and pair-based evaluation
• Clustering 9: image representation

IR15 Web Search and PageRank

IR15 Web Search and PageRank

• Web search 1: more data = higher precision
• Web search 2: big data beats clever algorithms
• Web search 3: introduction to PageRank
• Web search 4: PageRank algorithm: how it works
• Web search 5: PageRank at convergence
• Web search 6: PageRank using MapReduce
• Web search 7: sink nodes in PageRank
• Web search 8: hubs and authorities
• Web search 9: link spam
• Web search 10: anchor text

IR7 Inverted Indexing

IR7 Inverted Indexing

• Indexing 1: what makes google fast
• Indexing 2: inverted index
• Indexing 3: sparseness and linear merge
• Indexing 4: phrases and proximity
• Indexing 5: XML, structure and metadata
• Indexing 6: delta encoding (compression)
• Indexing 7: v-byte encoding (compression)
• Indexing 8: doc-at-a-time query execution
• Indexing 9: doc-at-a-time worst case
• Indexing 10: term-at-a-time query execution
• Indexing 11: query execution tradeoffs
• Indexing 12: expected cost of execution
• Indexing 13: heuristics for faster search
• Indexing 14: structured query execution
• Indexing 15: index construction
• Indexing 16: MapReduce
• Indexing 17: distributed search

IR13 Evaluating Search Engines

IR13 Evaluating Search Engines

• Evaluation 1: overview
• Evaluation 2: research hypotheses
• Evaluation 3: effectiveness vs. efficiency
• Evaluation 4: Cranfield paradigm
• Evaluation 5: relevance judgments
• Evaluation 6: precision and recall
• Evaluation 7: why we can’t use accuracy
• Evaluation 8: F-measure
• Evaluation 9: when recall/precision is misleading
• Evaluation 10: recall and precision over ranks
• Evaluation 11: interpolated recall-precision plot
• Evaluation 12: mean average precision
• Evaluation 13: MAP vs NDCG
• Evaluation 14: query logs and click deviation
• Evaluation 15: binary preference and Kendall tau
• Evaluation 16: hypothesis testing
• Evaluation 17: statistical significance test
• Evaluation 18: the sign test
• Evaluation 19: training / testing splits

IR10 Crawling the Web

IR10 Crawling the Web

• Web crawling 1: sources of data
• Web crawling 2: blogs, tweets, news feeds
• Web crawling 3: the algorithm
• Web crawling 4: inside an HTTP request
• Web crawling 5: robots.txt
• Web crawling 6: keeping index fresh

Google OR-Tools: Combinatorial Optimization

Solvers:

• Constraint Programming
• Linear and Mixed-Integer Programming
• Vehicle Routing
• Graph Algorithms

Content:

• Linear Optimization
• Constraint Optimization
• Integer Optimization
• Routing
• Bin Packing
• Network Flows
• Assignment
• Scheduling

Qt5 C++ GUI Programming

Qt5 C++ GUI Programming

• Qt5 C++ Tutorial Installation With Visual Studio 2015
• Qt5 C++ Tutorial Hello World Console Application #2
• Qt5 C++ Tutorial First GUI Application Window #3
• Qt5 C++ Signal And Slots With Practical Examples #4
• Qt5 C++ Creating Layouts #5
• Qt5 C++ Adding CSS Styles #6
• Qt5 C++ PushButton #7
• Qt5 C++ Create CheckBox #8
• Qt5 C++ Creating RadioButton #9
• Qt5 C++ ComboBox With Signal And Slots (programming) #10
• Qt5 C++ Creating ListWidget Application #11
• Qt5 C++ MessageBox Practical Example #12
• Qt5 C++ Creating Menu And Toolbar QMenu #13
• Qt5 C++ Creating Print Dialog (QPrintDialog) #14
• Qt5 C++ Creating Font Dialog (QFontDialog) #15
• Qt5 C++ Creating Color Dialog (QColorDialog) #16
• Qt5 C++ Creating File Dialog (QFileDialog) #17
• Qt5 C++ Progressbar And Slider (QProgressbar And QSlider) #18
• Qt5 C++ Creating Animations (QPropertyAnimation) #19
• Qt5 C++ Controlling Animation With Easing CurveQPropertyAnimation & QEasingCurve #20
• Qt5 C++ Creating Parallel Animation Group QParallelAnimationGroup #21
• Qt5 C++ Creating Sequential Animation Group (QSequentialAnimationGroup) #22
• Qt5 C++ How To Create State Machine In Qt (QStateMachine, QEventTransition) #23
• Qt5 C++ Drawing Text And Line (QPainter, QPen, QTextDocument) In Qt #24
• Qt5 C++ Drawing Rectangle (QPainter, QPen, QBrush) In Qt #25
• Qt5 C++ Drawing Ellipse (QPainter, QPen, QBrush) In Qt #26
• Qt5 C++ Gradients (QLinearGradients, QRadialGradient, QConicalGradient) #27
• Qt5 C++ Connecting Qt Application To Mysql Database #28
• Qt5 C++ How To Connect Qt Application To Sqlite3 Database #29
• Qt5 C++ Register & Login System With Mysql Main Design Part One #30
• Qt5 C++ Register & Login System With Mysql Main Design Part Two #31
• Qt5 C++ Register & Login System Inserting Users Data In To Mysql Part Three #32
• Qt5 C++ Register & Login System User Login Part Four (Mysql Database) #33
• Qt5 C++ QSqlQueryModel With Mysql Database & QTableView #34
• Qt5 C++ QSqlTableModel With Mysql Database & QTableView #35
• Qt5 C++ Creating BarChart With QtChart | C++ GUI Tutorial
• Qt5 C++ Creating LineChart With QtChart | C++ GUI Tutorial
• Qt5 C++ Creating PieChart With QtChart | C++ GUI Tutorial
• Qt5 C++ Creating DonutChart With QtChart

Developing QtQuick QML Applications in Qt5

Developing QtQuick QML Applications in Qt5

• QtQuick QML Introduction #1
• QtQuick QML First Window #2
• QtQuick QML Our First Rectangle #3
• QtQuick QML MouseArea #4
• QtQuick QML Properties #5
• QtQuick QML Scripting #6
• QtQuick QML Image Element #7

Qt5 C++ Charts

Qt5 C++ Charts

• Qt5 C++ Creating BarChart With QtChart
• Qt5 C++ Creating LineChart With QtChart
• Qt5 C++ Creating PieChart With QtChart
• Qt5 C++ Creating DonutChart With QtChart

Qt5 C++ OPENGL PROGRAMMING (OpenGL 2)

Qt5 C++ OPENGL PROGRAMMING

• 1 Qt5 C++ Opengl Tutorial Creating Window
• 2 Qt5 C++ Opengl Tutorial Drawing Quads
• 3 Qt5 C++ Opengl Tutorial Drawing Traingle And Coloring
• 4 Qt5 C++ Opengl Tutorial Rendering 3D Shape In Screen

Multivariable calculus

Multivariable calculus

• Multivariable functions | Multivariable calculus |
• Representing points in 3d | Multivariable calculus |
• Introduction to 3d graphs | Multivariable calculus |
• Interpreting graphs with slices | Multivariable calculus |
• Contour plots | Multivariable calculus |
• Parametric curves | Multivariable calculus |
• Parametric surfaces | Multivariable calculus |
• Vector fields, introduction | Multivariable calculus |
• Fluid flow and vector fields | Multivariable calculus |
• 3d vector fields, introduction | Multivariable calculus |
• 3d vector field example | Multivariable calculus |
• Transformations, part 1 | Multivariable calculus |
• Transformations, part 2 | Multivariable calculus |
• Transformations, part 3 | Multivariable calculus |
• Partial derivatives, introduction
• Partial derivatives and graphs
• Formal definition of partial derivatives
• Symmetry of second partial derivatives
• Gradient
• Gradient and graphs
• Directional derivative
• Directional derivative, formal definition
• Directional derivatives and slope
• Why the gradient is the direction of steepest ascent
• Gradient and contour maps
• Position vector valued functions | Multivariable Calculus |
• Derivative of a position vector valued function | Multivariable Calculus |
• Differential of a vector valued function | Multivariable Calculus |
• Vector valued function derivative example | Multivariable Calculus |
• Multivariable chain rule
• Multivariable chain rule intuition
• Vector form of the multivariable chain rule
• Multivariable chain rule and directional derivatives
• More formal treatment of multivariable chain rule
• Curvature intuition
• Curvature formula, part 1
• Curvature formula, part 2
• Curvature formula, part 3
• Curvature formula, part 4
• Curvature formula, part 5
• Curvature of a helix, part 1
• Curvature of a helix, part 2
• Curvature of a cycloid
• Computing the partial derivative of a vector-valued function
• Partial derivative of a parametric surface, part 1
• Partial derivative of a parametric surface, part 2
• Partial derivatives of vector fields
• Partial derivatives of vector fields, component by component
• Divergence intuition, part 1
• Divergence intuition, part 2
• Divergence formula, part 1
• Divergence formula, part 2
• Divergence example
• Divergence notation
• 2d curl intuition
• 2d curl formula
• 2d curl example
• 2d curl nuance
• Describing rotation in 3d with a vector
• 3d curl intuition, part 1
• 3d curl intuition, part 2
• 3d curl formula, part 1
• 3d curl formula, part 2
• 3d curl computation example
• Laplacian intuition
• Laplacian computation example
• Explicit Laplacian formula
• Harmonic Functions
• Jacobian prerequisite knowledge
• Local linearity for a multivariable function
• The Jacobian matrix
• Computing a Jacobian matrix
• The Jacobian Determinant
• What is a tangent plane
• Controlling a plane in space
• Computing a tangent plane
• Local linearization
• What do quadratic approximations look like
• Quadratic approximation formula, part 1
• Quadratic approximation formula, part 2
• Quadratic approximation example
• The Hessian matrix
• Expressing a quadratic form with a matrix
• Vector form of multivariable quadratic approximation
• Multivariable maxima and minima
• Saddle points
• Warm up to the second partial derivative test
• Second partial derivative test
• Second partial derivative test intuition
• Second partial derivative test example, part 1
• Second partial derivative test example, part 2
• Constrained optimization introduction
• Lagrange multipliers, using tangency to solve constrained optimization
• Finishing the intro lagrange multiplier example
• Lagrange multiplier example, part 1
• Lagrange multiplier example, part 2
• The Lagrangian
• Meaning of Lagrange multiplier
• Proof for the meaning of Lagrange multipliers | Multivariable Calculus |
• Introduction to the line integral | Multivariable Calculus |
• Line integral example 1 | Line integrals and Green’s theorem | Multivariable Calculus |
• Line integral example 2 (part 1) | Multivariable Calculus |
• Line integral example 2 (part 2) | Multivariable Calculus |
• Line integrals and vector fields | Multivariable Calculus |
• Using a line integral to find the work done by a vector field example |
• Parametrization of a reverse path |
• Scalar field line integral independent of path direction | Multivariable Calculus |
• Vector field line integrals dependent on path direction | Multivariable Calculus |
• Path independence for line integrals | Multivariable Calculus |
• Closed curve line integrals of conservative vector fields | Multivariable Calculus |
• Example of closed line integral of conservative field | Multivariable Calculus |
• Second example of line integral of conservative vector field | Multivariable Calculus |
• Double integral 1 | Double and triple integrals | Multivariable Calculus |
• Double integrals 2 | Double and triple integrals | Multivariable Calculus |
• Double integrals 3 | Double and triple integrals | Multivariable Calculus |
• Double integrals 4 | Double and triple integrals | Multivariable Calculus |
• Double integrals 5 | Double and triple integrals | Multivariable Calculus |
• Double integrals 6 | Double and triple integrals | Multivariable Calculus |
• Triple integrals 1 | Double and triple integrals | Multivariable Calculus |
• Triple integrals 2 | Double and triple integrals | Multivariable Calculus |
• Triple integrals 3 | Double and triple integrals | Multivariable Calculus |
• Introduction to parametrizing a surface with two parameters | Multivariable Calculus |
• Determining a position vector-valued function for a parametrization of two parameters |
• Partial derivatives of vector-valued functions | Multivariable Calculus |
• Introduction to the surface integral | Multivariable Calculus |
• Example of calculating a surface integral part 1 | Multivariable Calculus |
• Example of calculating a surface integral part 2 | Multivariable Calculus |
• Example of calculating a surface integral part 3 | Multivariable Calculus |
• Surface integral example part 1: Parameterizing the unit sphere |
• Surface integral example part 2: Calculating the surface differential |
• Surface integral example part 3: The home stretch | Multivariable Calculus |
• Surface integral ex2 part 1: Parameterizing the surface | Multivariable Calculus |
• Surface integral ex2 part 2: Evaluating integral | Multivariable Calculus |
• Surface integral ex3 part 1: Parameterizing the outside surface |
• Surface integral ex3 part 2: Evaluating the outside surface | Multivariable Calculus |
• Surface integral ex3 part 3: Top surface | Multivariable Calculus |
• Surface integral ex3 part 4: Home stretch | Multivariable Calculus |
• Conceptual understanding of flux in three dimensions | Multivariable Calculus |
• Constructing a unit normal vector to a surface | Multivariable Calculus |
• Vector representation of a surface integral | Multivariable Calculus |
• Green’s theorem proof part 1 | Multivariable Calculus |
• Green’s theorem proof (part 2) | Multivariable Calculus |
• Green’s theorem example 1 | Multivariable Calculus |
• Green’s theorem example 2 | Multivariable Calculus |
• Constructing a unit normal vector to a curve | Multivariable Calculus |
• 2D divergence theorem | Line integrals and Green’s theorem | Multivariable Calculus |
• Conceptual clarification for 2D divergence theorem | Multivariable Calculus |
• Stokes’ theorem intuition | Multivariable Calculus |
• Green’s and Stokes’ theorem relationship | Multivariable Calculus |
• Orienting boundary with surface | Multivariable Calculus |
• Orientation and stokes | Multivariable Calculus |
• Conditions for stokes theorem | Multivariable Calculus |
• Stokes example part 1 | Multivariable Calculus |
• Stokes example part 2: Parameterizing the surface | Multivariable Calculus |
• Stokes example part 3: Surface to double integral | Multivariable Calculus |
• Stokes example part 4: Curl and final answer | Multivariable Calculus |
• Evaluating line integral directly – part 1 | Multivariable Calculus |
• Evaluating line integral directly – part 2 | Multivariable Calculus |
• 3D divergence theorem intuition | Divergence theorem | Multivariable Calculus |
• Divergence theorem example 1 | Divergence theorem | Multivariable Calculus |
• Stokes’ theorem proof part 1 | Multivariable Calculus |
• Stokes’ theorem proof part 2 | Multivariable Calculus |
• Stokes’ theorem proof part 3 | Multivariable Calculus |
• Stokes’ theorem proof part 4 | Multivariable Calculus |
• Stokes’ theorem proof part 5 | Multivariable Calculus |
• Stokes’ theorem proof part 6 | Multivariable Calculus |
• Stokes’ theorem proof part 7 | Multivariable Calculus |
• Type I regions in three dimensions | Divergence theorem | Multivariable Calculus |
• Type II regions in three dimensions | Divergence theorem | Multivariable Calculus |
• Type III regions in three dimensions | Divergence theorem | Multivariable Calculus |
• Divergence theorem proof (part 1) | Divergence theorem | Multivariable Calculus |
• Divergence theorem proof (part 2) | Divergence theorem | Multivariable Calculus |
• Divergence theorem proof (part 3) | Divergence theorem | Multivariable Calculus |
• Divergence theorem proof (part 4) | Divergence theorem | Multivariable Calculus |
• Divergence theorem proof (part 5) | Divergence theorem | Multivariable Calculus |

Neural networks

Neural networks

• But what is a Neural Network? | Deep learning, chapter 1
• Gradient descent, how neural networks learn | Deep learning, chapter 2
• What is backpropagation really doing? | Deep learning, chapter 3
• Backpropagation calculus | Deep learning, chapter 4

Essence of calculus

Essence of calculus

• The Essence of Calculus, Chapter 1
• The paradox of the derivative | Essence of calculus, chapter 2
• Derivative formulas through geometry | Essence of calculus, chapter 3
• Visualizing the chain rule and product rule | Essence of calculus, chapter 4
• What’s so special about Euler’s number e? | Essence of calculus, chapter 5
• Implicit differentiation, what’s going on here? | Essence of calculus, chapter 6
• Limits, L’Hopital’s rule, and epsilon delta definitions | Essence of calculus, chapter 7
• Integration and the fundamental theorem of calculus | Essence of calculus, chapter 8
• What does area have to do with slope? | Essence of calculus, chapter 9
• Higher order derivatives | Essence of calculus, chapter 10
• Taylor series | Essence of calculus, chapter 11
• What they won’t teach you in calculus

Differential equations

Differential equations

• Differential equations, studying the unsolvable | DE1
• But what is a partial differential equation? | DE2
• Solving the heat equation | DE3
• But what is a Fourier series? From heat flow to circle drawings | DE4
• Understanding e to the i pi in 3.14 minutes | DE5

Essence of linear algebra

Essence of linear algebra

• Vectors, what even are they? | Essence of linear algebra, chapter 1
• Linear combinations, span, and basis vectors | Essence of linear algebra, chapter 2
• Linear transformations and matrices | Essence of linear algebra, chapter 3
• Matrix multiplication as composition | Essence of linear algebra, chapter 4
• Three-dimensional linear transformations | Essence of linear algebra, chapter 5
• The determinant | Essence of linear algebra, chapter 6
• Inverse matrices, column space and null space | Essence of linear algebra, chapter 7
• Nonsquare matrices as transformations between dimensions | Essence of linear algebra, chapter 8
• Dot products and duality | Essence of linear algebra, chapter 9
• Cross products | Essence of linear algebra, Chapter 10
• Cross products in the light of linear transformations | Essence of linear algebra chapter 11
• Cramer’s rule, explained geometrically | Essence of linear algebra, chapter 12
• Change of basis | Essence of linear algebra, chapter 13
• Eigenvectors and eigenvalues | Essence of linear algebra, chapter 14
• Abstract vector spaces | Essence of linear algebra, chapter 15